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Record W1580984542 · doi:10.1002/path.4344

Targeted next‐generation sequencing of cancer genes dissects the molecular profiles of intraductal papillary neoplasms of the pancreas

2014· article· en· W1580984542 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Pathology · 2014
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsUniversity Hospital Foundation
FundersNational Center for Advancing Translational SciencesUniversità degli Studi di VeronaRolfe Pancreatic Cancer FoundationNational Institutes of HealthNational Cancer InstituteAssociazione Italiana per la Ricerca sul Cancro
KeywordsGNAS complex locusKRASIntraductal papillary mucinous neoplasmDysplasiaCancerPathologyGene mutationPancreasCancer researchMedicineCarcinomaMutationBiologyGeneInternal medicineColorectal cancerGenetics

Abstract

fetched live from OpenAlex

Intraductal neoplasms are important precursors to invasive pancreatic cancer and provide an opportunity to detect and treat pancreatic neoplasia before an invasive carcinoma develops. The diagnostic evaluation of these lesions is challenging, as diagnostic imaging and cytological sampling do not provide accurate information on lesion classification, the grade of dysplasia or the presence of invasion. Moreover, the molecular driver gene mutations of these precursor lesions have yet to be fully characterized. Fifty-two intraductal papillary neoplasms, including 48 intraductal papillary mucinous neoplasms (IPMNs) and four intraductal tubulopapillary neoplasms (ITPNs), were subjected to the mutation assessment in 51 cancer-associated genes, using ion torrent semiconductor-based next-generation sequencing. P16 and Smad4 immunohistochemistry was performed on 34 IPMNs and 17 IPMN-associated carcinomas. At least one somatic mutation was observed in 46/48 (96%) IPMNs; 29 (60%) had multiple gene alterations. GNAS and/or KRAS mutations were found in 44/48 (92%) of IPMNs. GNAS was mutated in 38/48 (79%) IPMNs, KRAS in 24/48 (50%) and these mutations coexisted in 18/48 (37.5%) of IPMNs. RNF43 was the third most commonly mutated gene and was always associated with GNAS and/or KRAS mutations, as were virtually all the low-frequency mutations found in other genes. Mutations in TP53 and BRAF genes (10% and 6%) were only observed in high-grade IPMNs. P16 was lost in 7/34 IPMNs and 9/17 IPMN-associated carcinomas; Smad4 was lost in 1/34 IPMNs and 5/17 IPMN-associated carcinomas. In contrast to IPMNs, only one of four ITPNs had detectable driver gene (GNAS and NRAS) mutations. Deep sequencing DNA from seven cyst fluid aspirates identified 10 of the 13 mutations detected in their associated IPMN. Using next-generation sequencing to detect cyst fluid mutations has the potential to improve the diagnostic and prognostic stratification of pancreatic cystic neoplasms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.320
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it